Facies Classification and Prediction to Improve Understanding of Reservoir Heterogeneities

Pattern recognition in data mining has proven to be a valuable addition to Quantitative Seismic Interpretation methods, for improving understanding of the reservoir depositional system and reservoir properties. This presentation displays some of Paradigm’s seismic attribute calculation and amplitude inversion technologies, constrained by geological information, for enhanced qualitative and quantitative reservoir characterization.  The implementation of seismic facies classification methods demonstrates the benefits of artificial intelligence when extracting information about reservoir lithology.  The combination of multiple seismic attributes with well information provides a deeper understanding of reservoir rock properties in terms of facies distribution, porosity estimation, and fluid content.